Neutrality and variability: two sides of evolvability in linear genetic programming

@InProceedings{DBLP:conf/gecco/HuB09,
author = "Ting Hu and Wolfgang Banzhaf",
title = "Neutrality and variability: two sides of evolvability
in linear genetic programming",
booktitle = "GECCO '09: Proceedings of the 11th Annual conference
on Genetic and evolutionary computation",
year = "2009",
editor = "Guenther Raidl and Franz Rothlauf and
Giovanni Squillero and Rolf Drechsler and Thomas Stuetzle and
Mauro Birattari and Clare Bates Congdon and
Martin Middendorf and Christian Blum and Carlos Cotta and
Peter Bosman and Joern Grahl and Joshua Knowles and
David Corne and Hans-Georg Beyer and Ken Stanley and
Julian F. Miller and Jano {van Hemert} and
Tom Lenaerts and Marc Ebner and Jaume Bacardit and
Michael O'Neill and Massimiliano {Di Penta} and Benjamin Doerr and
Thomas Jansen and Riccardo Poli and Enrique Alba",
pages = "963--970",
address = "Montreal",
publisher = "ACM",
publisher_address = "New York, NY, USA",
month = "8-12 " # jul,
organisation = "SigEvo",
keywords = "genetic algorithms, genetic programming",
isbn13 = "978-1-60558-325-9",
bibsource = "DBLP, http://dblp.uni-trier.de",
DOI = "doi:10.1145/1569901.1570033",
abstract = "The notion of evolvability has been put forward to
describe the {"}core mechanism{"} of natural and
artificial evolution. Recently, studies have revealed
the influence of the environment upon a system's
evolvability. In this contribution, we study the
evolvability of a system in various environmental
situations. We consider neutrality and variability as
two sides of evolvability. The former makes a system
tolerant to mutations and provides a hidden staging
ground for future phenotypic changes. The latter
produces explorative variations yielding phenotypic
improvements. Which of the two dominates is influenced
by the environment. We adopt two tools for this study
of evolvability: 1) the rate of adaptive evolution,
which captures the observable adaptive variations
driven by evolvability; and 2) the variability of
individuals, which measures the potential of an
individual to vary functionally. We apply these tools
to a Linear Genetic Programming system and observe that
evolvability is able to exploit its two sides in
different environmental situations.",
notes = "GECCO-2009 A joint meeting of the eighteenth
international conference on genetic algorithms
(ICGA-2009) and the fourteenth annual genetic
programming conference (GP-2009).
ACM Order Number 910092.",
}